Changes in Light Pollution and the Causing Factors in China's Protected Areas, 1992-2012

The natural nighttime light environment of the earth has been significantly transformed by human activities. Such “light pollution” has a profound influence on ecosystems. Protected areas (PAs) play key ecological functions and are only effective at low light pollution levels or without any light pollution. In China, with rapid population growth and high urbanization rates, light pollution in PAs continues to aggravate and threaten a number of ecosystems. We used calibrated nighttime light images to study spatial-temporal changes in light pollution in China’s PAs from 1992 to 2012 by classifying light pollution into three levels (moderate, medium, and strong). The results showed that in China’s PAs, the area subject to light pollution increased by about 1.79 times, with a significant increase in the intensity of artificial light. The changes in light pollution exhibited significant regional differences. In the eastern developed regions, light pollution was more significant than that in other regions and the situation in East China was the most severe. In the Qinghai-Tibet, although light pollution was less significant, the area subject to light pollution increased significantly over the evaluated period. Factors influencing light pollution were also analyzed. Light pollution in a PA is influenced by both human activities and its own characteristics.

[1]  Christian Wolter,et al.  Light pollution as a biodiversity threat. , 2010, Trends in ecology & evolution.

[2]  Christian Wolter,et al.  Aerial survey and spatial analysis of sources of light pollution in Berlin, Germany , 2012 .

[3]  M. Bennett,et al.  Advances in using multitemporal night-time lights satellite imagery to detect, estimate, and monitor socioeconomic dynamics , 2017 .

[4]  M. J. Butt Estimation of Light Pollution Using Satellite Remote Sensing and Geographic Information System Techniques , 2012 .

[5]  Osamu Higashi,et al.  A SVM-based method to extract urban areas from DMSP-OLS and SPOT VGT data , 2009 .

[6]  Jiyuan Liu,et al.  Spatiotemporal characteristics, patterns, and causes of land-use changes in China since the late 1980s , 2014, Journal of Geographical Sciences.

[7]  Mikhail Zhizhin,et al.  A Fifteen Year Record of Global Natural Gas Flaring Derived from Satellite Data , 2009 .

[8]  Jin Chen,et al.  Modelling the population density of China at the pixel level based on DMSP/OLS non‐radiance‐calibrated night‐time light images , 2009 .

[9]  Karen C. Seto,et al.  Monitoring urbanization dynamics in India using DMSP/OLS night time lights and SPOT-VGT data , 2013, Int. J. Appl. Earth Obs. Geoinformation.

[10]  S. Sulliván,et al.  Bright lights, big city: influences of ecological light pollution on reciprocal stream-riparian invertebrate fluxes. , 2013, Ecological applications : a publication of the Ecological Society of America.

[11]  Curtis H. Flather,et al.  Housing growth in and near United States protected areas limits their conservation value , 2009, Proceedings of the National Academy of Sciences.

[12]  M. Tan Urban Growth and Rural Transition in China Based on DMSP/OLS Nighttime Light Data , 2015 .

[13]  J. A. Quintanilha,et al.  DMSP/OLS night‐time light imagery for urban population estimates in the Brazilian Amazon , 2006 .

[14]  Travis Longcore,et al.  Ecological light pollution , 2004 .

[15]  Xia Cao,et al.  Policy and regulatory responses to coalmine closure and coal resources consolidation for sustainability in Shanxi, China , 2017 .

[16]  Zhifeng Liu,et al.  Urban expansion dynamics and natural habitat loss in China: a multiscale landscape perspective , 2014, Global change biology.

[17]  P. Sutton,et al.  Radiance Calibration of DMSP-OLS Low-Light Imaging Data of Human Settlements , 1999 .

[18]  Xiangzheng Deng,et al.  Growth, population and industrialization, and urban land expansion of China , 2008 .

[19]  Minghong Tan,et al.  Use of an inside buffer method to extract the extent of urban areas from DMSP/OLS nighttime light data in North China , 2016 .

[20]  W. Nordhaus,et al.  Using luminosity data as a proxy for economic statistics , 2011, Proceedings of the National Academy of Sciences.

[21]  Li Junsheng,et al.  Distribution of terrestrial national nature reserves in relation to human activities and natural environments in China: Distribution of terrestrial national nature reserves in relation to human activities and natural environments in China , 2014 .

[22]  Jinliang Huang,et al.  Monitoring Trends in Light Pollution in China Based on Nighttime Satellite Imagery , 2014, Remote. Sens..

[23]  Erik Lichtenberg,et al.  Local officials as land developers: Urban spatial expansion in China , 2009 .

[24]  Minghong Tan,et al.  An Intensity Gradient/Vegetation Fractional Coverage Approach to Mapping Urban Areas From DMSP/OLS Nighttime Light Data , 2017, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.

[25]  Zhifeng Liu,et al.  Extracting the dynamics of urban expansion in China using DMSP-OLS nighttime light data from 1992 to 2008 , 2012 .

[26]  Paul C. Sutton,et al.  A scale-adjusted measure of Urban sprawl using nighttime satellite imagery , 2003 .

[27]  K. Gaston,et al.  Quantifying the erosion of natural darkness in the global protected area system , 2015, Conservation biology : the journal of the Society for Conservation Biology.

[28]  K. Gaston,et al.  Contrasting trends in light pollution across Europe based on satellite observed night time lights , 2014, Scientific Reports.

[29]  Kevin J. Gaston,et al.  Human alteration of natural light cycles: causes and ecological consequences , 2014, Oecologia.

[30]  Boulder,et al.  The first World Atlas of the artificial night sky brightness , 2001, astro-ph/0108052.

[31]  Chaolang Hua,et al.  Identifying local-scale wilderness for on-ground conservation actions within a global biodiversity hotspot , 2016, Scientific Reports.